Abstract: A system for health monitoring comprised of one or more neural networks. A first function of the one or more neural networks includes an autoencoder functionality, tuned to have high recall, configured for monitoring data and for detecting an anomaly within the data. A second function of the one or more neural networks is a false positive reduction (FPR) function, configured for distinguishing false positive anomalies from true positive anomalies by analyzing the data or querying an individual. Confirmed positive anomalies are classified by a classification engine. The system may be configured to train one or more machine learning models thereof, such that the system is trained for monitoring of the individual.

Abstract: A system for management of health conditions, such as mental health conditions, using a biosensor configured to monitor one or more biological properties of an individual and providing feedback and information based on data in real-time. A corresponding method, performed by one or more components of the system, may include monitoring abiological property of the individual, identifying an irregularity as a symptom of the health condition, and intervening with the individual to alleviate the symptom. The method may further include determining an efficacy of the intervention and adapting the method to improve the intervention. The system may be configured to predict a future symptom and preventatively intervene.

Abstract: A smart home interaction system is presented. It is built on a multi-modal, multithreaded conversational dialog engine. The system provides a natural language user interface for the control of household devices, appliances or household functionality. The smart home automation agent can receive input from users through sensing devices such as a smart phone, a tablet computer or a laptop computer. Users interact with the system from within the household or from remote locations. The smart home system can receive input from sensors or any other machines with which it is interfaced. The system employs interaction guide rules for processing reaction to both user and sensor input and driving the conversational interactions that result from such input. The system adaptively learns based on both user and sensor input and can learn the preferences and practices of its users.

Abstract: A Mechanical Turk—Integrated Development Environment system is disclosed. An integrated development environment (IDE) can include one or more interfaces capable of communicating with a mechanical turk engine. As a developer creates applications within the IDE, the developer can use the IDE to submit one or more requests to the mechanical turk engine. The engine constructs a mechanical turk project based on the requests and provides project tasks to workers. The results of the tasks can then be compiled and integrated back into the developer's application via the IDE. An example use includes constructing large domain specific data sets that can be applied to spoken dialog interfaces.

Abstract: A device capable of splitting user input into phrases is presented. The disclosed device leverages multiple phrase splitting models to generate one or more possible split locations. The possible split locations can be derived based on leveraging multiple phrase splitting models. Each model contributes its suggested split locations to the set of possible split locations according to an implementation of a phrase splitting kernel algorithm that weights each model's suggestions.

Abstract: The invention enables creation of grammar networks that can regulate, control, and define the content and scope of human-machine interaction in natural language voice user interfaces (NLVUI). More specifically, the invention concerns a phrase-based modeling of generic structures of verbal interaction and use of these models for the purpose of automating part of the design of such grammar networks.

Abstract: A device capable of splitting user input into phrases is presented. The disclosed device leverages multiple phrase splitting models to generate one or more possible split locations. The possible split locations can be derived based on leveraging multiple phrase splitting models. Each model contributes its suggested split locations to the set of possible split locations according to an implementation of a phrase splitting kernel algorithm that weights each model's suggestions.

Abstract: A smart home interaction system is presented. It is built on a multi-modal, multithreaded conversational dialog engine. The system provides a natural language user interface for the control of household devices, appliances or household functionality. The smart home automation agent can receive input from users through sensing devices such as a smart phone, a tablet computer or a laptop computer. Users interact with the system from within the household or from remote locations. The smart home system can receive input from sensors or any other machines with which it is interfaced. The system employs interaction guide rules for processing reaction to both user and sensor input and driving the conversational interactions that result from such input. The system adaptively learns based on both user and sensor input and can learn the preferences and practices of its users.

Abstract: A smart home interaction system is presented. It is built on a multi-modal, multithreaded conversational dialog engine. The system provides a natural language user interface for the control of household devices, appliances or household functionality. The smart home automation agent can receive input from users through sensing devices such as a smart phone, a tablet computer or a laptop computer. Users interact with the system from within the household or from remote locations. The smart home system can receive input from sensors or any other machines with which it is interfaced. The system employs interaction guide rules for processing reaction to both user and sensor input and driving the conversational interactions that result from such input. The system adaptively learns based on both user and sensor input and can learn the preferences and practices of its users.

Abstract: A device capable of splitting user input into phrases is presented. The disclosed device leverages multiple phrase splitting models to generate one or more possible split locations. The possible split locations can be derived based on leveraging multiple phrase splitting models. Each model contributes its suggested split locations to the set of possible split locations according to an implementation of a phrase splitting kernel algorithm that weights each model's suggestions.

Abstract: A Mechanical Turk—Integrated Development Environment system is disclosed. An integrated development environment (IDE) can include one or more interfaces capable of communicating with a mechanical turk engine. As a developer creates applications within the IDE, the developer can use the IDE to submit one or more requests to the mechanical turk engine. The engine constructs a mechanical turk project based on the requests and provides project tasks to workers. The results of the tasks can then be compiled and integrated back into the developer's application via the IDE. An example use includes constructing large domain specific data sets that can be applied to spoken dialog interfaces.

Abstract: A Mechanical Turk-Integrated Development Environment system is disclosed. An integrated development environment (IDE) can include one or more interfaces capable of communicating with a mechanical turk engine. As a developer creates applications within the IDE, the developer can use the IDE to submit one or more requests to the mechanical turk engine. The engine constructs a mechanical turk project based on the requests and provides project tasks to workers. The results of the tasks can then be compiled and integrated back into the developer's application via the IDE. An example use includes constructing large domain specific data sets that can be applied to spoken dialog interfaces.

Abstract: A smart home interaction system is presented. It is built on a multi-modal, multithreaded conversational dialog engine. The system provides a natural language user interface for the control of household devices, appliances or household functionality. The smart home automation agent can receive input from users through sensing devices such as a smart phone, a tablet computer or a laptop computer. Users interact with the system from within the household or from remote locations. The smart home system can receive input from sensors or any other machines with which it is interfaced. The system employs interaction guide rules for processing reaction to both user and sensor input and driving the conversational interactions that result from such input. The system adaptively learns based on both user and sensor input and can learn the preferences and practices of its users.

Abstract: A smart home interaction system is presented. It is built on a multi-modal, multithreaded conversational dialog engine. The system provides a natural language user interface for the control of household devices, appliances or household functionality. The smart home automation agent can receive input from users through sensing devices such as a smart phone, a tablet computer or a laptop computer. Users interact with the system from within the household or from remote locations. The smart home system can receive input from sensors or any other machines with which it is interfaced. The system employs interaction guide rules for processing reaction to both user and sensor input and driving the conversational interactions that result from such input. The system adaptively learns based on both user and sensor input and can learn the preferences and practices of its users.

Abstract: A Mechanical Turk-Integrated Development Environment system is disclosed. An integrated development environment (IDE) can include one or more interfaces capable of communicating with a mechanical turk engine. As a developer creates applications within the IDE, the developer can use the IDE to submit one or more requests to the mechanical turk engine. The engine constructs a mechanical turk project based on the requests and provides project tasks to workers. The results of the tasks can then be compiled and integrated back into the developer's application via the IDE. An example use includes constructing large domain specific data sets that can be applied to spoken dialog interfaces.

Abstract: A Mechanical Turk-Integrated Development Environment system is disclosed. An integrated development environment (IDE) can include one or more interfaces capable of communicating with a mechanical turk engine. As a developer creates applications within the IDE, the developer can use the IDE to submit one or more requests to the mechanical turk engine. The engine constructs a mechanical turk project based on the requests and provides project tasks to workers. The results of the tasks can then be compiled and integrated back into the developer's application via the IDE. An example use includes constructing large domain specific data sets that can be applied to spoken dialog interfaces.

Abstract: The performance of traditional speech recognition systems (as applied to information extraction or translation) decreases significantly with, larger domain size, scarce training data as well as under noisy environmental conditions. This invention mitigates these problems through the introduction of a novel predictive feature extraction method which combines linguistic and statistical information for representation of information embedded in a noisy source language. The predictive features are combined with text classifiers to map the noisy text to one of the semantically or functionally similar groups. The features used by the classifier can be syntactic, semantic, and statistical.

Abstract: A device capable of splitting user input into phrases is presented. The disclosed device leverages multiple phrase splitting models to generate one or more possible split locations. The possible split locations can be derived based on leveraging multiple phrase splitting models. Each model contributes its suggested split locations to the set of possible split locations according to an implementation of a phrase splitting kernel algorithm that weights each model's suggestions.

Abstract: Interpretation from a first language to a second language via one or more communication devices is performed through a communication network (e.g. phone network or the internet) using a server for performing recognition and interpretation tasks, comprising the steps of: receiving an input speech utterance in a first language on a first mobile communication device; conditioning said input speech utterance; first transmitting said conditioned input speech utterance to a server; recognizing said first transmitted speech utterance to generate one or more recognition results; interpreting said recognition results to generate one or more interpretation results in an interlingua; mapping the interlingua to a second language in a first selected format; second transmitting said interpretation results in the first selected format to a second mobile communication device; and presenting said interpretation results in a second selected format on said second communication device.

Abstract: The invention enables creation of grammar networks that can regulate, control, and define the content and scope of human-machine interaction in natural language voice user interfaces (NLVUI). The invention enables phrase-based modeling of generic structures of verbal interaction to be used for the purpose of automating part of the design of such grammar networks. Most particularly, the invention enables such grammar networks to be used in providing a voice-controlled user interface to human readable text data that is also machine-readable (such as a Web page, a word processing document, a PDF document, or a spreadsheet).